计算机科学
推论
分析
数据科学
互联网
索引(排版)
移动设备
代理(哲学)
万维网
互联网接入
视觉分析
Web应用程序
社会经济地位
机器学习
大数据
宽带
数据挖掘
信息物理系统
云计算
人工智能
Web映射
预测分析
支持向量机
移动电话技术
作者
Elijah Knodel,David J. Wald,Vincent Quitoriano,Sabine Loos
摘要
Abstract The U.S. Geological Survey’s (USGS) “Did You Feel It?” (DYFI) system is an internet tool that collects shaking intensity observations through crowdsourcing. It produces maps and provides supplementary data to ShakeMap, which offers near-real-time maps of ground motion resulting from significant earthquakes around the globe. Barriers such as technology and language make DYFI an unequally accessible tool, however, leading to a less comprehensive view of an earthquake’s impact in certain regions. Here, we analyze users’ global interaction with DYFI to evaluate its accessibility. We employ web analytics to quantify how users access DYFI, and perform inference modeling to predict each country’s response rate to DYFI. The panel dataset built for this inference model combines physical earthquake parameters from the USGS with socioeconomic data from the World Bank and the Central Intelligence Agency for 151 countries from 2009 to 2020. Our web analytics show that users predominantly access DYFI through mobile devices and are often referred through social media. In addition, results from the inference model reveal that socioeconomic parameters, including primary language spoken and broadband internet subscriptions, alongside physical earthquake parameters such as average shaking intensity, have a significant effect on a country’s response rate to DYFI. As a result of this analysis, we establish a country priority index for improved DYFI awareness and accessibility. This index considers regions of the world lacking seismic station coverage that face barriers to DYFI access, such as language, technology, and other factors. Consequently, the USGS has made evaluating DYFI’s performance on mobile devices a priority and has begun incorporating and monitoring the use of additional languages within the DYFI system. Furthermore, our analyses suggest specific nations with low response rates could benefit from targeted outreach in conjunction with partner agencies in each country.
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